Please use this identifier to cite or link to this item: https://doi.org/10.1081/DRT-200059138
Title: Modeling intermittent drying using an adaptive neuro-fuzzy inference system
Authors: Jumah, R.
Mujumdar, A.S. 
Keywords: Fuzzy logic
Intermittent drying
Neural networks
Spouted beds
Issue Date: 2005
Source: Jumah, R., Mujumdar, A.S. (2005). Modeling intermittent drying using an adaptive neuro-fuzzy inference system. Drying Technology 23 (5) : 1075-1092. ScholarBank@NUS Repository. https://doi.org/10.1081/DRT-200059138
Abstract: Artificial intelligence systems such as artificial neural networks (ANN) and fuzzy inference systems (FIS) are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. The advantages of a combination of ANN and FIS are obvious. This article presents the application of a hybrid neuro-fuzzy system called adaptive-network-based fuzzy inference system (ANFIS) to time dependent drying processes and is illustrated by an application to model intermittent drying of grains in a spouted bed. An introduction to the ANFIS modeling approach is also presented. The model showed good performance in terms of various statistical indices. Copyright © 2005 Taylor & Francis, Inc.
Source Title: Drying Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/60790
ISSN: 07373937
DOI: 10.1081/DRT-200059138
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